Huperzine A(HupA) is a highly selective, reversible acetylcholinesterase(AChE) inhibitor that exhibits neuroprotective effects and is clinically used to manage benign memory decline.However, the specific relationship ...Huperzine A(HupA) is a highly selective, reversible acetylcholinesterase(AChE) inhibitor that exhibits neuroprotective effects and is clinically used to manage benign memory decline.However, the specific relationship between the pharmacokinetic(PK) profile of HupA and cerebral acetylcholine(ACh) dynamics remains poorly characterized. Here, we characterize the PK-pharmacodynamic(PD) properties of HupA in rats under both physiological and pathological conditions. Following a single intramuscular injection, HupA exhibits a short halflife but rapid brain penetration, while multiple dosing significantly enhances its brain exposure. In a middle cerebral artery occlusion(MCAO) rat model, HupA demonstrates increased brain distribution. Furthermore, HupA elevates ACh concentrations across multiple brain regions, concurrently modulating several monoamine neurotransmitters. Using a minimal physiologically based pharmacokinetic-pharmacodynamic(mPBPK-PD) modeling approach,cerebral ACh dynamics were accurately predicted based on the pharmacokinetics of HupA in systemic circulation. The developed mPBPK-PD model exhibits robust predictive performance and holds potential for guiding the optimization of clinical dosing regimens and improving the therapeutic efficacy of HupA.展开更多
Cardiac injury initiates repair mechanisms and results in cardiac remodeling and fi-brosis,which appears to be a leading cause of cardiovascular diseases.Cardiac fi-brosis is characterized by the accumulation of extra...Cardiac injury initiates repair mechanisms and results in cardiac remodeling and fi-brosis,which appears to be a leading cause of cardiovascular diseases.Cardiac fi-brosis is characterized by the accumulation of extracellular matrix proteins,mainly collagen in the cardiac interstitium.Many experimental studies have demonstrated that fibrotic injury in the heart is reversible;therefore,it is vital to understand differ-ent molecular mechanisms that are involved in the initiation,progression,and resolu-tion of cardiac fibrosis to enable the development of antifibrotic agents.Of the many experimental models,one of the recent models that has gained renewed interest is isoproterenol(ISP)-induced cardiac fibrosis.ISP is a synthetic catecholamine,sympa-thomimetic,and nonselectiveβ-adrenergic receptor agonist.The overstimulated and sustained activation ofβ-adrenergic receptors has been reported to induce biochemi-cal and physiological alterations and ultimately result in cardiac remodeling.ISP has been used for decades to induce acute myocardial infarction.However,the use of low doses and chronic administration of ISP have been shown to induce cardiac fibrosis;this practice has increased in recent years.Intraperitoneal or subcutaneous ISP has been widely used in preclinical studies to induce cardiac remodeling manifested by fibrosis and hypertrophy.The induced oxidative stress with subsequent perturbations in cellular signaling cascades through triggering the release of free radicals is consid-ered the initiating mechanism of myocardial fibrosis.ISP is consistently used to induce fibrosis in laboratory animals and in cardiomyocytes isolated from animals.In recent years,numerous phytochemicals and synthetic molecules have been evaluated in ISP-induced cardiac fibrosis.The present review exclusively provides a comprehensive summary of the pathological biochemical,histological,and molecular mechanisms of ISP in inducing cardiac fibrosis and hypertrophy.It also summarizes the application of this experimental model in the therapeutic evaluation of natural as well as syn-thetic compounds to demonstrate their potential in mitigating myocardial fibrosis and hypertrophy.展开更多
Objective:To analyze the positive impact of pharmaceutical care in the ophthalmology perioperative period on the rational use of antibiotics.Methods:A total of 115 patients who underwent ophthalmological surgery betwe...Objective:To analyze the positive impact of pharmaceutical care in the ophthalmology perioperative period on the rational use of antibiotics.Methods:A total of 115 patients who underwent ophthalmological surgery between March and June 2023 were selected as the control group,receiving routine medication management.Another 115 patients who underwent ophthalmological surgery between July and October 2023 were selected as the observation group,receiving pharmaceutical care.The rationality of medication use,mastery of medication knowledge,medication compliance,and adverse reaction rates were compared between the two groups.Results:The observation group had higher rationality of medication use,higher scores for mastery of medication knowledge,higher medication compliance,and a lower adverse reaction rate compared to the control group(P<0.05).Conclusion:The combination of antibiotic therapy and pharmaceutical care in the ophthalmology perioperative period can improve the rationality of medication use,enhance patients’mastery of medication knowledge,increase their medication compliance,and prevent adverse reactions to antibiotics.展开更多
Objective To study the current situation of China’s pharmacovigilance system,and to provide some suggestions for the improvement of related policies.Methods A policy modeling consistency(PMC)index model of pharmacovi...Objective To study the current situation of China’s pharmacovigilance system,and to provide some suggestions for the improvement of related policies.Methods A policy modeling consistency(PMC)index model of pharmacovigilance policy was constructed to quantitatively assess the samples of policies combining text mining.Then,the PMC surface was established to obtain the visualization results of China’s pharmacovigilance policy samples,and their shortcomings were clearly analyzed by comparison.Results and Conclusion Forty-one percent of China’s pharmacovigilance policies were rated as excellent,54%as acceptable,and the overall evaluation was acceptable.But there is still some room for improvement.On the whole,there are problems of insufficient policy synergy,lack of policy incentives and constraints,and incomplete coverage of policy functions.It is recommended that China’s pharmacovigilance policy system should be optimized by strengthening policy coordination,increasing policy incentives and constraints,and guiding multi-subjects to participate in coordination.These findings and recommendations can provide operational ideas for the system of China’s pharmacovigilance policy.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Objective To provide effective decision making for the subsidy policies given by the government to pharmaceutical enterprises and the coordination model adopted by pharmaceutical stakeholders under the carbon emission...Objective To provide effective decision making for the subsidy policies given by the government to pharmaceutical enterprises and the coordination model adopted by pharmaceutical stakeholders under the carbon emission trading policy.Methods The Stackelberg model was used to discuss the optimal profits of each member and the whole supply chain under different decision-making models while considering the technical capacity of emission reduction and cost sharing contract.Based on this,the impact of the combined contract decisionmaking model on the technical efforts of drug manufacturers to reduce carbon emission,the profits of supply chain members and the overall profits of supply chain was investigated.Results and Conclusion Research has found that improving the research and development efforts of emission reduction technologies by pharmaceutical enterprises can increase drug sales and enhance the expected profits of pharmaceutical supply chain members.The members of the secondary pharmaceutical supply chain can achieve the optimal expected profit when reaching cooperation.Besides,when the cost sharing contract and quantity discount contract meet the constraint conditions,the combined contract decision model can perfectly coordinate the pharmaceutical supply chain,enabling supply chain members to achieve Pareto improvement and gradually reach Pareto optimum.展开更多
Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the prefere...Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the preferences of Chinese dermatologists regarding LLM-generated responses in clinical psoriasis scenarios and to assess how they prioritize key quality dimensions,including accuracy,traceability,and logicality.Methods:A cross-sectional,web-based survey was conducted between December 25,2024,and January 22,2025,following the Checklist for Reporting Results of Internet E-Surveys guidelines.A total of 1247 valid responses were collected from practicing dermatologists across 33 of China's provincial-level administrative divisions.Participants evaluated responses to five categories of clinical questions(etiology,clinical presentation,differential diagnosis,treatment,and case study)generated by five LLMs:ChatGPT-4o,Kimi.ai,Doubao,ZuoYiGPT,and Lingyi-agent.Statistical associations between participant characteristics and model preferences were examined using chi-square tests.Results:ChatGPT-4o(Model 1)emerged as the most preferred model across all clinical tasks,consistently receiving the highest number of votes in case study(n=740),clinical presentation(n=666),differential diagnosis(n=707),etiology(n=602),and treatment(n=656).Significant variation in model preference by professional title was observed only for the differential diagnosis task(χ^(2)=21.13,df=12,p=0.0485),while no significant differences were found across hospital tiers(p>0.05).In terms of evaluation dimensions,accuracy was most frequently rated as“very important”(n=635).A significant association existed between hospital tier and the most valued dimension(χ^(2)=27.667,df=9,p=0.0011),with dermatologists in primary hospitals prioritizing traceability more than their peers in higher-tier hospitals.No significant associations were found across professional titles(p=0.127).Conclusions:Chinese dermatologists suggest a strong preference for ChatGPT-4o over domestic LLMs in psoriasis-related clinical tasks.While accuracy remains the primary criterion,traceability and logicality are also critical,particularly for clinicians in lower-tier hospitals.These findings suggest that future clinical LLMs should prioritize not only content accuracy but also source transparency and structural clarity to meet the diverse needs of different clinical settings.展开更多
The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpec...The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpected non-physical phase points in practice.We conduct an analysis on the phase-space characteristics and the fixed-point theory underlying the k-ε turbulence model,and employ the classical Kolmogorov flow as a framework,leveraging its direct numerical simulation(DNS)data to construct a one-dimensional(1D)system under periodic/fixed boundary conditions.The RANS results demonstrate that under periodic boundary conditions,the k-ε model exhibits only a unique trivial fixed point,with asymptotes capturing the phase portraits.The stability of this trivial fixed point is determined by a mathematically derived stability phase diagram,indicating the fact that the k-ε model will never converge to correct values under periodic conditions.In contrast,under fixed boundary conditions,the model can yield a stable non-trivial fixed point.The evolutionary mechanisms and their relationship with boundary condition settings systematically explain the inherent limitations of the k-ε model,i.e.,its deficiency in computing the flow field under periodic boundary conditions and sensitivity to boundary-value specifications under fixed boundary conditions.These conclusions are finally validated with the open-source code OpenFOAM.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
Coordinate transformation models often fail to account for nonlinear and spatially dependent distortions,leading to significant residual errors in geospatial applications.Here,we propose a residual-based neural correc...Coordinate transformation models often fail to account for nonlinear and spatially dependent distortions,leading to significant residual errors in geospatial applications.Here,we propose a residual-based neural correction(RBNC)strategy,in which a neural network learns to model only the systematic distortions left by an initial geometric transformation.By focusing solely on residual patterns,RBNC reduces model complexity and improves performance,particularly in scenarios with sparse or structured control point configurations.We evaluate the method using both simulated datasets(with varying distortion intensities and sampling strategies)and real-world image georeferencing tasks.Compared with direct neural network coordinate converters and classical transformation models,RBNC delivers more accurate and stable results under challenging conditions,while maintaining comparable performance in ideal cases.These findings demonstrate the effectiveness of residual modelling as a light-weight and robust alternative for improving coordinate transformation accuracy.展开更多
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-bas...The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow ...Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow River Basin.Using the‘cupball'model,this study analyzes the limiting factors and restoration characteristics across four mining areas and proposes a conceptual model for selecting appropriate restoration approaches.A second conceptual model is then introduced to address regional development needs,incorporating ecological conservation,safety protection,and people's wellbeing.The applicability of the integrated model selection framework is demonstrated through a case study on the south bank of the Qinglongjian River.The results indicate that:(1)The key limiting factors are similar across cases,but the degree of ecological degradation varies.(2)Mildly degraded areas are represented by a shallower and narrower‘cup',where natural recovery is the preferred approach,whereas moderately and severely degraded systems call for assisted regeneration and ecological reconstruction,respectively.(3)When the restoration models determined based on limiting factors and development needs are consistent,the model is directly applicable;if they differ,the option involving less artificial intervention is preferred;(4)Monitoring of the restored mining area on the Qinglongjian River's south bank confirms significant improvements in soil erosion control and vegetation coverage.This study provides a transferable methodology for balancing resource extraction with ecosystem conservation,offering practical insights for other ecologically vulnerable mining regions.展开更多
基金supported by the National Key Research and Development Program of China (No. 2024YFA1308200)the National Natural Science Foundation of China (Nos. 82274009 and81973556)。
文摘Huperzine A(HupA) is a highly selective, reversible acetylcholinesterase(AChE) inhibitor that exhibits neuroprotective effects and is clinically used to manage benign memory decline.However, the specific relationship between the pharmacokinetic(PK) profile of HupA and cerebral acetylcholine(ACh) dynamics remains poorly characterized. Here, we characterize the PK-pharmacodynamic(PD) properties of HupA in rats under both physiological and pathological conditions. Following a single intramuscular injection, HupA exhibits a short halflife but rapid brain penetration, while multiple dosing significantly enhances its brain exposure. In a middle cerebral artery occlusion(MCAO) rat model, HupA demonstrates increased brain distribution. Furthermore, HupA elevates ACh concentrations across multiple brain regions, concurrently modulating several monoamine neurotransmitters. Using a minimal physiologically based pharmacokinetic-pharmacodynamic(mPBPK-PD) modeling approach,cerebral ACh dynamics were accurately predicted based on the pharmacokinetics of HupA in systemic circulation. The developed mPBPK-PD model exhibits robust predictive performance and holds potential for guiding the optimization of clinical dosing regimens and improving the therapeutic efficacy of HupA.
基金United Arab Emirates University,Grant/Award Number:12R104 and 12R121。
文摘Cardiac injury initiates repair mechanisms and results in cardiac remodeling and fi-brosis,which appears to be a leading cause of cardiovascular diseases.Cardiac fi-brosis is characterized by the accumulation of extracellular matrix proteins,mainly collagen in the cardiac interstitium.Many experimental studies have demonstrated that fibrotic injury in the heart is reversible;therefore,it is vital to understand differ-ent molecular mechanisms that are involved in the initiation,progression,and resolu-tion of cardiac fibrosis to enable the development of antifibrotic agents.Of the many experimental models,one of the recent models that has gained renewed interest is isoproterenol(ISP)-induced cardiac fibrosis.ISP is a synthetic catecholamine,sympa-thomimetic,and nonselectiveβ-adrenergic receptor agonist.The overstimulated and sustained activation ofβ-adrenergic receptors has been reported to induce biochemi-cal and physiological alterations and ultimately result in cardiac remodeling.ISP has been used for decades to induce acute myocardial infarction.However,the use of low doses and chronic administration of ISP have been shown to induce cardiac fibrosis;this practice has increased in recent years.Intraperitoneal or subcutaneous ISP has been widely used in preclinical studies to induce cardiac remodeling manifested by fibrosis and hypertrophy.The induced oxidative stress with subsequent perturbations in cellular signaling cascades through triggering the release of free radicals is consid-ered the initiating mechanism of myocardial fibrosis.ISP is consistently used to induce fibrosis in laboratory animals and in cardiomyocytes isolated from animals.In recent years,numerous phytochemicals and synthetic molecules have been evaluated in ISP-induced cardiac fibrosis.The present review exclusively provides a comprehensive summary of the pathological biochemical,histological,and molecular mechanisms of ISP in inducing cardiac fibrosis and hypertrophy.It also summarizes the application of this experimental model in the therapeutic evaluation of natural as well as syn-thetic compounds to demonstrate their potential in mitigating myocardial fibrosis and hypertrophy.
文摘Objective:To analyze the positive impact of pharmaceutical care in the ophthalmology perioperative period on the rational use of antibiotics.Methods:A total of 115 patients who underwent ophthalmological surgery between March and June 2023 were selected as the control group,receiving routine medication management.Another 115 patients who underwent ophthalmological surgery between July and October 2023 were selected as the observation group,receiving pharmaceutical care.The rationality of medication use,mastery of medication knowledge,medication compliance,and adverse reaction rates were compared between the two groups.Results:The observation group had higher rationality of medication use,higher scores for mastery of medication knowledge,higher medication compliance,and a lower adverse reaction rate compared to the control group(P<0.05).Conclusion:The combination of antibiotic therapy and pharmaceutical care in the ophthalmology perioperative period can improve the rationality of medication use,enhance patients’mastery of medication knowledge,increase their medication compliance,and prevent adverse reactions to antibiotics.
文摘Objective To study the current situation of China’s pharmacovigilance system,and to provide some suggestions for the improvement of related policies.Methods A policy modeling consistency(PMC)index model of pharmacovigilance policy was constructed to quantitatively assess the samples of policies combining text mining.Then,the PMC surface was established to obtain the visualization results of China’s pharmacovigilance policy samples,and their shortcomings were clearly analyzed by comparison.Results and Conclusion Forty-one percent of China’s pharmacovigilance policies were rated as excellent,54%as acceptable,and the overall evaluation was acceptable.But there is still some room for improvement.On the whole,there are problems of insufficient policy synergy,lack of policy incentives and constraints,and incomplete coverage of policy functions.It is recommended that China’s pharmacovigilance policy system should be optimized by strengthening policy coordination,increasing policy incentives and constraints,and guiding multi-subjects to participate in coordination.These findings and recommendations can provide operational ideas for the system of China’s pharmacovigilance policy.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Objective To provide effective decision making for the subsidy policies given by the government to pharmaceutical enterprises and the coordination model adopted by pharmaceutical stakeholders under the carbon emission trading policy.Methods The Stackelberg model was used to discuss the optimal profits of each member and the whole supply chain under different decision-making models while considering the technical capacity of emission reduction and cost sharing contract.Based on this,the impact of the combined contract decisionmaking model on the technical efforts of drug manufacturers to reduce carbon emission,the profits of supply chain members and the overall profits of supply chain was investigated.Results and Conclusion Research has found that improving the research and development efforts of emission reduction technologies by pharmaceutical enterprises can increase drug sales and enhance the expected profits of pharmaceutical supply chain members.The members of the secondary pharmaceutical supply chain can achieve the optimal expected profit when reaching cooperation.Besides,when the cost sharing contract and quantity discount contract meet the constraint conditions,the combined contract decision model can perfectly coordinate the pharmaceutical supply chain,enabling supply chain members to achieve Pareto improvement and gradually reach Pareto optimum.
基金National Key Research and Development Program of China,Grant/Award Number:2024YFF0507404Special Clinical Business Fund for High-Level Hospitals of China-Japan Friendship Hospital,Grant/Award Number:2024-NHLHCRF-TS-01。
文摘Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the preferences of Chinese dermatologists regarding LLM-generated responses in clinical psoriasis scenarios and to assess how they prioritize key quality dimensions,including accuracy,traceability,and logicality.Methods:A cross-sectional,web-based survey was conducted between December 25,2024,and January 22,2025,following the Checklist for Reporting Results of Internet E-Surveys guidelines.A total of 1247 valid responses were collected from practicing dermatologists across 33 of China's provincial-level administrative divisions.Participants evaluated responses to five categories of clinical questions(etiology,clinical presentation,differential diagnosis,treatment,and case study)generated by five LLMs:ChatGPT-4o,Kimi.ai,Doubao,ZuoYiGPT,and Lingyi-agent.Statistical associations between participant characteristics and model preferences were examined using chi-square tests.Results:ChatGPT-4o(Model 1)emerged as the most preferred model across all clinical tasks,consistently receiving the highest number of votes in case study(n=740),clinical presentation(n=666),differential diagnosis(n=707),etiology(n=602),and treatment(n=656).Significant variation in model preference by professional title was observed only for the differential diagnosis task(χ^(2)=21.13,df=12,p=0.0485),while no significant differences were found across hospital tiers(p>0.05).In terms of evaluation dimensions,accuracy was most frequently rated as“very important”(n=635).A significant association existed between hospital tier and the most valued dimension(χ^(2)=27.667,df=9,p=0.0011),with dermatologists in primary hospitals prioritizing traceability more than their peers in higher-tier hospitals.No significant associations were found across professional titles(p=0.127).Conclusions:Chinese dermatologists suggest a strong preference for ChatGPT-4o over domestic LLMs in psoriasis-related clinical tasks.While accuracy remains the primary criterion,traceability and logicality are also critical,particularly for clinicians in lower-tier hospitals.These findings suggest that future clinical LLMs should prioritize not only content accuracy but also source transparency and structural clarity to meet the diverse needs of different clinical settings.
基金Project supported by the National Natural Science Foundation of China(Nos.12372214 and U2341231)。
文摘The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpected non-physical phase points in practice.We conduct an analysis on the phase-space characteristics and the fixed-point theory underlying the k-ε turbulence model,and employ the classical Kolmogorov flow as a framework,leveraging its direct numerical simulation(DNS)data to construct a one-dimensional(1D)system under periodic/fixed boundary conditions.The RANS results demonstrate that under periodic boundary conditions,the k-ε model exhibits only a unique trivial fixed point,with asymptotes capturing the phase portraits.The stability of this trivial fixed point is determined by a mathematically derived stability phase diagram,indicating the fact that the k-ε model will never converge to correct values under periodic conditions.In contrast,under fixed boundary conditions,the model can yield a stable non-trivial fixed point.The evolutionary mechanisms and their relationship with boundary condition settings systematically explain the inherent limitations of the k-ε model,i.e.,its deficiency in computing the flow field under periodic boundary conditions and sensitivity to boundary-value specifications under fixed boundary conditions.These conclusions are finally validated with the open-source code OpenFOAM.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
基金National Council for Scientific and Technological Development,Grant No.421278/2023-4,No.309248/2025-6。
文摘Coordinate transformation models often fail to account for nonlinear and spatially dependent distortions,leading to significant residual errors in geospatial applications.Here,we propose a residual-based neural correction(RBNC)strategy,in which a neural network learns to model only the systematic distortions left by an initial geometric transformation.By focusing solely on residual patterns,RBNC reduces model complexity and improves performance,particularly in scenarios with sparse or structured control point configurations.We evaluate the method using both simulated datasets(with varying distortion intensities and sampling strategies)and real-world image georeferencing tasks.Compared with direct neural network coordinate converters and classical transformation models,RBNC delivers more accurate and stable results under challenging conditions,while maintaining comparable performance in ideal cases.These findings demonstrate the effectiveness of residual modelling as a light-weight and robust alternative for improving coordinate transformation accuracy.
基金supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
基金supported by the CAS Pioneer Hundred Talents Program and Second Tibetan Plateau Scientific Expedition Research Program(2019QZKK0708)as well as the Basic Research Program of Qinghai Province:Lithospheric Geomagnetic Field of the Qinghai-Tibet Plateau and the Relationship with Strong Earthquakes(2021-ZJ-969Q).
文摘The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
基金supported by Special major projects for research and development of Henan Provincial(Science and Technology Research Project)(No.252102321104)Humanities and Social Sciences Youth Foundation,Ministry of Education(24YJCZH410)。
文摘Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow River Basin.Using the‘cupball'model,this study analyzes the limiting factors and restoration characteristics across four mining areas and proposes a conceptual model for selecting appropriate restoration approaches.A second conceptual model is then introduced to address regional development needs,incorporating ecological conservation,safety protection,and people's wellbeing.The applicability of the integrated model selection framework is demonstrated through a case study on the south bank of the Qinglongjian River.The results indicate that:(1)The key limiting factors are similar across cases,but the degree of ecological degradation varies.(2)Mildly degraded areas are represented by a shallower and narrower‘cup',where natural recovery is the preferred approach,whereas moderately and severely degraded systems call for assisted regeneration and ecological reconstruction,respectively.(3)When the restoration models determined based on limiting factors and development needs are consistent,the model is directly applicable;if they differ,the option involving less artificial intervention is preferred;(4)Monitoring of the restored mining area on the Qinglongjian River's south bank confirms significant improvements in soil erosion control and vegetation coverage.This study provides a transferable methodology for balancing resource extraction with ecosystem conservation,offering practical insights for other ecologically vulnerable mining regions.
